2023-02-02 Implementing a retinotopic transform using grid_sample from pyTorch
Implementing a retinotopic transform using grid_sample from pyTorch¶
The grid_sample transform is a powerful function which allows to transform any input image into a new topology. It is notably used in Spatial Transformer Networks for instance to learn CNN to be invariant to affine transforms. We used it recently in a publication What You See Is What You Transform: Foveated Spatial Transformers as a Bio-Inspired Attention Mechanism by Ghassan Dabane et al.
The use of grid_sample can b etedious and here, we show how to use it to create a log-polar transform of the image and create the following figure:

A picture (extract from the painting "The Ambassadors" by Hans Holbein the Younger can be represented on a regular grid represented by vertical (red) and horizontal (blue) lines. Retinotopy transforms this grid, and in particular the area representing the fovea (shaded gray) is over-represented. Applied to the original image of the portrait, the image is strongly distorted and represents more finally the parts under the axis of sight (here the mouth).


qui montre une nette séparation des groupes de vote.





























